Group Meetings
Besides updating each other on the latest from our individual projects, we try to get young scientists from other research groups to come and share their work with us.
Currently our group meetings take place every Friday at 10 am CEST and goes on till around 12 noon. Since the beginning of November 2020, the meetings are entirely on Zoom.
Topic: MLCS Group Meeting
Time: Fridays, 10 am CEST
Join Zoom Meeting: Send email
Upcoming
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11 June 2021
Intro to the ML Cloud SLURM queue
Discussion led by Felix Strnad
MLCS -
18 June 2021
IMPRS Boot Camp -
25 June 2021
Reservoir computing with swarms
Thomas Lymburn
University of Western Australia -
2 July 2021
Interpretable neural networks to identify which density Information determines the state of the AMOC
Björn Mayer
Climate Modelling, Institute of Oceanography, Universität Hamburg -
9 July 2021
Prediction of soil type maps using uncertainty
Kerstin Rau
Soil Science and Geomorphology, University of Tübingen -
14 July 2021 (Guest Lecture for ML-4430 course)
TBA
Peter Dueben
Earth System Modelling Seciton, ECMFW -
23 July 2021
TBA -
30 July 2021
TBA
Past Meetings
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4 June 2021
Curvature-based analysis of climate networks
Christian Fröhlich
MLCS -
28 May 2021
Analysing tropical - extratropical teleconnection in boreal summer with causal maps: ERA-I vs SEAS5
Giorgia Di Capua
ESMO, PIK Potsdam -
21 May 2021
Get-to-Know & Informal discussion -
14 May 2021
Ensemble Prediction
Online Public Lecture by Tim Palmer
Perspectives Climate - 7 May 2021
Application of edit distance method to recurrence plot and climate network
Abhirup Banerjee
Complexity Science, PIK Potsdam - 30 April 2021
vEGU 2021 - 23 April 2021
vEGU 2021 - 16 April 2021
Trial Talks for #vEGU2021
Presentation by Members of MLCS - 9 April 2021, 9 AM CEST (!)
Developing a novel hydrological proxy from trace metals in stalagmites
Sebastian Höpker
Waikato Environmental Geochemistry - 2 April 2021
Good Friday - 26 March 2021
Collective learning for a sustainable future
Wolfram Barfuss
School of Mathematics, University of Leeds - 19 March 2021, 16:00 CET (!)
Fingerprint of volcanic forcing on the ENSO-Indian Monsoon coupling
Manmeet Singh
IITM Pune - 12 March 2021
Generative adversarial training for simulation-based inference
Poornima Ramesh
Machine Learning in Science - 5 March 2021
At the intersection of climate science, machine learning and Earth system dynamics
Sebastian Mutz
Palaeoclimate and Climate Dynamics Jr. Research group - 26 February 2021
Variations of wind convergence in context of ITCZ
Lea Elsemüller
Machine Learning in Climate Science - 19 February 2021
Constraining ice shelf basalt melt rates from isochrone data
Vjeran Visnjevic
Glaciology and Geophysics Group - 12 February 2021
A brief introduction to recurrence plot based analysis
Bedartha Goswami
Machine Learning in Climate Science - 5 February 2021
Impact of strong El Niño events on river discharge in South America
Markus Deppner
Machine Learning in Climate Science - 29 January 2021
An Introduction to Digital Soil Mapping
Ruhollah Taghizadeh-Mehrjardi
Department of Soil Science and Geomorphology - 22 January 2021
How Artificial Intelligence could help mitigate climate change
Online Public Lecture
Climate Change AI - 15 January 2021
Disentangling the latent space representation of Pacific sea surface temperature anomalies
Jakob Schlör
Machine Learning in Climate Science - 8 January 2021
Analyzing the monsoon by networks of extreme rainfall events
Felix Strnad
Machine Learning in Climate Science - 1 January 2021
New Year - 25 December 2020
Christmas - 18 December 2020
Laplace Matching for generalized linear models
Marius Hobbhahn
Methods of Machine Learning - 11 December 2020
Modeling Spatiotemporal Dynamics with a Neural Network Architecture
Matthias Karlbauer
Neuro-Cognitive Modeling Group - 4 December 2020
Uncovering the inductive bias of NetGAN
Luca Rendsburg
Theory of Machine Learning - 27 November 2020
Probabilistic models in network analysis
Martina Contisciani
Physics for Inference and Optimization - 20 November 2020
Gaussian Processes for parameter estimation of PDEs
Thomas Gläßle
Methods of Machine Learning - 13 November 2020
Update on projects
Markus Deppner, Lea Elsemueller
MLCS